Marta Lovino
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Postdoctoral Research Position in NLP for Clinical Data and Transformer-Based Explainable AI University of Modena and Reggio Emilia in Italy
Degree Level
Postdoc
Field of study
Computer Science
Funding
1-year research/postdoctoral position. Salary starts at approximately €1,600 net per month and increases according to experience and profile.
Country
Italy
University
University of Modena and Reggio Emilia

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About this position
Postdoctoral research position in Natural Language Processing, Machine Learning, Deep Learning, and Transformer-based models for real-world clinical data.
The role focuses on developing and applying NLP methods for longitudinal patient data, with an emphasis on explainability and support for clinical decision-making. The work is described as a close collaboration between AI researchers and clinicians, using real-world clinical data with direct clinical relevance.
Location: Modena, Italy, at the University of Modena and Reggio Emilia.
Eligibility: Candidates should have a solid background in AI/Machine Learning, strong Python skills, and experience with deep learning, Transformers, and NLP. Backgrounds in Computer Science, Bioinformatics, Biomedical Engineering, or related areas are welcome.
Funding: 1-year research/postdoctoral position with salary starting at approximately €1,600 net/month, increasing according to experience and profile.
How to apply: Email your CV and a short description of your research interests to Marta Lovino at [email protected].
Funding details
1-year research/postdoctoral position. Salary starts at approximately €1,600 net per month and increases according to experience and profile.
What's required
Solid background in AI/Machine Learning and strong Python skills. Experience with deep learning, Transformers, and NLP is required. Backgrounds in Computer Science, Bioinformatics, Biomedical Engineering, or related fields are welcome.
How to apply
Send your CV and a short description of your research interests by email to Marta Lovino. The post invites interested candidates to get in touch directly and to share the opportunity with others.
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